Subsea 7 Beneish M-Score Historical Data
The historical data trend for Subsea 7's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
Subsea 7 Beneish M-Score Chart
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Subsea 7 Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.60 |
-5.48 |
-3.17 |
-2.91 |
-2.31 |
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Subsea 7 Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.70 |
-2.56 |
-2.55 |
-2.31 |
-2.32 |
Competitive Comparison of Subsea 7's Beneish M-Score
For the Oil & Gas Equipment & Services subindustry, Subsea 7's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Subsea 7's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, Subsea 7's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Subsea 7's Beneish M-Score falls into.
Subsea 7 Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of Subsea 7 for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 0.8823 | + | 0.528 * 1.2506 | + | 0.404 * 1.9182 | + | 0.892 * 1.2445 | + | 0.115 * 0.8648 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8364 | + | 4.679 * -0.086759 | - | 0.327 * 1.1723 |
| = | -2.32 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was kr21,346 Mil.
Revenue was 14808.124 + 17209.236 + 16925.722 + 16386.776 = kr65,330 Mil.
Gross Profit was 863.825 + 1196.302 + 1371.689 + 753.589 = kr4,185 Mil.
Total Current Assets was kr30,225 Mil.
Total Assets was kr86,823 Mil.
Property, Plant and Equipment(Net PPE) was kr48,550 Mil.
Depreciation, Depletion and Amortization(DDA) was kr5,951 Mil.
Selling, General, & Admin. Expense(SGA) was kr860 Mil.
Total Current Liabilities was kr28,206 Mil.
Long-Term Debt & Capital Lease Obligation was kr11,254 Mil.
Net Income was 286.527 + -182.505 + 368.93 + 196.494 = kr669 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = kr0 Mil.
Cash Flow from Operations was -140.08 + 5576.413 + 3100.511 + -334.688 = kr8,202 Mil.
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Total Receivables was kr19,441 Mil.
Revenue was 13126.405 + 12755.209 + 14458.813 + 12155.507 = kr52,496 Mil.
Gross Profit was 544.52 + 1686.533 + 1204.901 + 770.076 = kr4,206 Mil.
Total Current Assets was kr28,944 Mil.
Total Assets was kr78,647 Mil.
Property, Plant and Equipment(Net PPE) was kr45,903 Mil.
Depreciation, Depletion and Amortization(DDA) was kr4,787 Mil.
Selling, General, & Admin. Expense(SGA) was kr826 Mil.
Total Current Liabilities was kr21,582 Mil.
Long-Term Debt & Capital Lease Obligation was kr8,908 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (21346.239 / 65329.858) | / | (19440.519 / 52495.934) |
| = | 0.326746 | / | 0.370324 |
| | = | 0.8823 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (4206.03 / 52495.934) | / | (4185.405 / 65329.858) |
| = | 0.080121 | / | 0.064066 |
| | = | 1.2506 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (30225.383 + 48550.357) / 86822.896) | / | (1 - (28943.814 + 45902.923) / 78646.791) |
| = | 0.092685 | / | 0.048318 |
| | = | 1.9182 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 65329.858 | / | 52495.934 |
| | = | 1.2445 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (4786.658 / (4786.658 + 45902.923)) | / | (5951.264 / (5951.264 + 48550.357)) |
| = | 0.094431 | / | 0.109194 |
| | = | 0.8648 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (859.932 / 65329.858) | / | (826.131 / 52495.934) |
| = | 0.013163 | / | 0.015737 |
| | = | 0.8364 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((11254.132 + 28205.901) / 86822.896) | / | ((8908.219 + 21581.736) / 78646.791) |
| = | 0.454489 | / | 0.387682 |
| | = | 1.1723 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (669.446 - 0 | - | 8202.156) | / | 86822.896 |
| | = | -0.086759 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
Subsea 7 has a M-score of -2.32 suggests that the company is unlikely to be a manipulator.
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